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Uncertainty quantification in imaging and automatic horizon tracking: a
  Bayesian deep-prior based approach

Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approach

1 April 2020
Ali Siahkoohi
G. Rizzuti
Felix J. Herrmann
ArXivPDFHTML

Papers citing "Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approach"

3 / 3 papers shown
Title
Learned multiphysics inversion with differentiable programming and
  machine learning
Learned multiphysics inversion with differentiable programming and machine learning
M. Louboutin
Ziyi Yin
Rafael Orozco
Thomas J. Grady
Ali Siahkoohi
G. Rizzuti
Philipp A. Witte
O. Møyner
Gerard Gorman
Felix J. Herrmann
AI4CE
13
10
0
12 Apr 2023
Learning by example: fast reliability-aware seismic imaging with
  normalizing flows
Learning by example: fast reliability-aware seismic imaging with normalizing flows
Ali Siahkoohi
Felix J. Herrmann
OOD
27
13
0
13 Apr 2021
Stochastic seismic waveform inversion using generative adversarial
  networks as a geological prior
Stochastic seismic waveform inversion using generative adversarial networks as a geological prior
L. Mosser
O. Dubrule
M. Blunt
GAN
AI4CE
74
207
0
10 Jun 2018
1